Alternative Tracking Methodsfor Household Expenditure

Ravi P. Rannan-EliyaInstitute for Health Policy (IHP)

Sri Lanka

Consultation on National Health Accounts& External Resource Flows

Ellison Institute for World HealthAlexandria, VA

July 21-22, 2005

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Problems of Household SurveyData

Example: Sri Lanka

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Deaton (2003)

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Recall loss for hospitalizations

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Recent Estimation ExperienceProblems with household survey data

• Suffer from significant non-sampling errors• Eg: recall loss, telescoping, etc.

• Sampling errors if complete population is not covered• Existing surveys may lack sufficient detail to meet SHA

requirements• Surveys are costly, not timely, and are not available every year

Emerging approach• More intensive use of supply-side data and other projection

techniques, e.g., pharmaceutical retail sales data, revenue ofmedical providers, facility use statistics, etc

• Systematic quantification of non-sampling bias using independentdata, and adjustment of survey data

• Reliance on household survey data only for minor part ofestimations

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Household Spending in CanadaHospitalsCanadian MIS Database

Residential/nursinghomesSurvey of residential carefacilities

Medical suppliesAC Nielsen Canada

PharmaceuticalsIndustry data from ACNielsen Canada

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Household Spending in Sri LankaPublic sector user feesGovernment hospital data

Private hospitalsSpecial hospital survey,drug sales data

Western medicinesIndustry sales data, IMS

Private medicalpractitionersVarious data sources inc.drug sales data, utilizationsurveys, clinic surveys

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Household Spending in BangladeshPublic sector user feesOfficial revenue reports

Private hospitalsSurvey of privatehospitals/clinics

OTCs/PharmaceuticalsIndustry retail data from IMSBangladesh supplementedwith ndustry production data

NGOsSurvey of NGO healthservices

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Alternative Approach

Identical conceptually to those used inincome accounts

Production-side estimatesTriangulation

But does not imply that estimates areidentical to the national accounts

Health accounts can afford to devote moretechnical resources and exploit more datasources

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Existing Methods (1)Pharmaceuticals

Industry/production side retail dataIMS-Health (SL, Bangladesh, HK, Taiwan, Malaysia)AC Nielsen (Canada)Drug Accounts (Thailand)

Private hospitalsNational surveys of hospital revenues

USA, Bangladesh, Sri Lanka, Hong Kong, MongoliaTriangulation from insurance data

Australia, Taiwan

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Existing Methods (2)Private physicians

Tax data universally unreliable (including USA)Price * Quantity (PQ) approach

Use different surveys/sources to estimate P and QseparatelyHong Kong, Sri Lanka, Thailand, Malaysia

Traditional providers, dentists, paramedicalsSpecial surveys of providers, insurance data

Hong Kong, Korea, JapanTriangulation from household survey data

Calibrating using other reliable components

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Combining methods in composite trendestimate

Focus on estimating elements as time series, notsingle cell estimates (temporal consistency)Requirement that estimates be consistent withdata sources at multiple timesEmphasis on accuracy of trends, not just levelsFocus on understanding trends, not single yearcross-section

Existing Methods (3)

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Household Spending in Hong KongPublic sector user feesGovernment hospital data

Private hospitalsSpecial hospital survey,drug sales data

Private medicalpractitionersVarious data sources inc.drug sales data, tax returns,utilization surveys, doctorsurveys

Western medicinesIndustry sales data, IMS

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Duplicate measurement in theoryProblem: To estimate private clinic doctors revenues

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Duplicate measurement in practiceProblem: To estimate private clinic doctors revenues

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Duplicate measurement in practiceProblem: To estimate private clinic doctors revenues

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Duplicate measurement in practiceProblem: To estimate private clinic doctors revenues

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Duplicate measurement in practiceProblem: To estimate private clinic doctors revenues

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Trend Estimation ExampleHong Kong DHA: Comparison of estimates of private

doctors' revenues

-

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

9,000

10,000

1989 1990 1991 1992 1993 1994 1995 1996 1997

GHS 1992 GHS 1996 IMS and tax data

HES 90/95 Proposed DHA estimate

Example: Hong Kong

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IssuesCookbooks partially available (WHO PG, EurostatGuide)

Priority is to document existing sources outside OECDLack of OECD-type process outside OECD to improvemethods through cross-national discussion

Cookbook not sufficientExact methods will vary between country and over timeRequires capacity to evaluate, select and modify methodscontinuously

Scarcity and hidden nature of dataOften best overcome through multiple-year estimatesreconciling different data methodsDifficult to do well from outside country

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Agenda for future

Regional and global stock-taking ofmethods

Currently not fundedMeeting-based mechanisms for expertsoutside OECD to share, review andimprove methods on routine basis

Currently under-funded